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In an era where artificial intelligence (AI) is rapidly transforming business operations, the importance of Data Security Posture Management (DSPM) cannot be overstated.

Data Security Posture Management plays an important role in modern digital infrastructure by providing a comprehensive framework to manage and mitigate data security risks.

DSPM also helps in identifying and mitigating security risks associated with AI adoption along with ensuring that organizations can leverage AI technologies safely and effectively.

Key aspects of DSPM:

• 360-degree view approach for data at rest, in-transit, and risk associated to users.


• Centralized Visibility and monitoring approach into sensitive data, it’s usage and access across different systems.


• Regular risk assessments are performed to determine any vulnerabilities within the infrastructure 


• Direct integrations with various third-party tools and CSP’s

Exponential Increase in Data Threats

The rise of AI has brought about an exponential increase in data threats.

 Here are some alarming statistics:

• Data Security Incidents: A staggering 83% of organizations have experienced more than one data breach throughout their existence, underscoring the prevalence of security incidents.


• Insider Threats: Accounting for 20% of data breaches, insider threats pose significant risks, with the average cost to resolve such threats reaching $15.4 million over a 12-month period.


• Generative AI Concerns: The adoption of generative AI brings its own set of challenges, with over 80% of organizations expressing concerns about the potential leakage of sensitive data during the training and implementation phases.

Enhancing and securing Data Security with Microsoft Purview

Microsoft Purview offers an integrated solution for securing and governing data across multi-cloud and hybrid environments.

Its adaptive features continuously evaluate and adjust risk levels to prevent unauthorized data use. Here are some of the key features that play a crucial role in strengthening Data Security Posture:

Data Security:

• Data Loss Prevention: Safeguards data throughout its lifecycle, wherever it resides.


• Insider Risk Management: Addresses internal threats effectively.


• Information Protection: Ensures sensitive information remains confidential.

Data Governance:

• Data Discovery: Identifies and classifies data across the organization.


• Data Quality: Maintains the integrity and accuracy of data.


• Data Curation: Organizes and manages data for easy access and analysis.


• Data Estate Insights: Provides visibility into data usage and storage.

Data Compliance:

• Compliance Manager: Helps meet regulatory requirements and manage risks.


• eDiscovery and Audit: Facilitates legal investigations and compliance checks.


• Communication Compliance: Monitors and controls communication channels to prevent data leaks.


• Data Lifecycle Management: Manages the retention and deletion of data.


• Records Management: Ensures proper record-keeping for compliance and governance.

Conclusion

The integration of AI into business processes necessitates a robust approach to data security.

Data Security Posture Management, as part of an organization’s cybersecurity strategy, is critical for identifying, managing, and mitigating risks associated with AI adoption